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'I recently explored what Google searches tell us about depression, by which I mean, loosely, dips in mood. [I used] anonymous, aggregate data from tens of millions of queries.... thanks to the incredibly large sample size, meaningful patterns emerge. According to the data, depression is highest in April. Depression is lowest in August. The state with the highest rate of depression is North Dakota; the one with the lowest, Virginia. The city with the highest rate is Presque Isle, Me.; the city with the lowest, San Francisco. Depression is, unsurprisingly, highest on Mondays and lowest on Saturdays. The date on which depression is lowest is Dec. 25, followed by a few days surrounding it. The strongest predictor by far: an area's average temperature in January. Colder places have higher rates of depression, with the correlation concentrated in the colder months. Google searches, the biggest data source we currently have, are unambiguous: when it comes to our happiness, climate matters a great deal. There is a lesson here for public health and medical researchers. Are you investigating how weather affects migraine headaches? How chemicals in water affect autism rates? I believe we are about to enter a golden age of disease research. Many of the biggest developments will come from the analysis of big data, not from traditional experiments that survey a relatively small number of people.